Precise frequency estimation of short data bursts

ABSTRACT

The invention performs frequency estimation over both the burst preamble, during which known symbols are transmitted, and also during the burst&#39;s data packet, which is subsequent to the preamble and extracted by the local detector. During the preamble, an initial frequency estimate is obtained. This estimate is based on a time average of either phase or correlation samples. Atypical phase or correlation samples, attributable to detector symbol errors during the data packet, are detected and filtered, so as to avoid including the atypical samples in a time-averages used to provide the frequency estimate. In a first embodiment correlation samples are time averaged, and atypical correlation samples are suppressed prior to correlation time averaging. In a second embodiment, phase slope values are time averaged, and atypical values of phase slope are suppressed prior to phase slope time averaging.

CROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to the following internationalpatent application: European Application No. 01400495.6, entitled“PRECISE FREQUENCY ESTIMATION OF SHORT DATA BURSTS,” Ambroise Popper,filed Feb. 26, 2001.

BACKGROUND

[0002]FIGS. 1A and 1B illustrate a prior-art Hybrid Fiber-Coax (HFC)cable system 100 that is compatible with the cable industry standardData over Cable System Interface Specification (DOCSIS) for providingInternet access to cable customers via so called Cable Modems (CMs).FIG. 1A is a top-level view of the cable system. FIG. 1B providesadditional detail of the Customer Premises Equipment (CPE) of FIG. 1A.In FIG. 1B, CM 4000 provides a computer industry standard Ethernetinterface to PC 5000 and bridges the Ethernet interface with the coaxdistribution of the cable system. CM 4000 internally implements both anRF Modulator and an RF Demodulator for communications over the coax inaccordance with the DOCSIS standard.

[0003] An RF Modulator 3000 and RF Demodulator 1000, complementary tothose of the cable modem, are implemented in a DOCSIS compatible CableModem Termination System (CMTS) 500, which as the name implies, providestermination for the Cable Modem of the CPE. Multiple instances ofModulator 3000 and Demodulator 1000 are provisioned to support allcustomers with CM service. Control, MAC, Framing 2000 bridges all of theprovisioned DOCSIS RF interfaces with one or more packet-based networks.These packet networks may include local area networks, intranets, andthe Internet. While FIG. 1A shows the CMTS 500 implemented in a Head Endor Primary Hub, theoretically it is possible to implement the CMTSanywhere upstream from the CM. Each demodulator 1000 provides outputs tothe Control, MAC, Framing 2000 that include Detected Symbols 1200 and aFrequency Offset Estimate 1300.

[0004] While the transmitter of the CM upstream modulator and thecomplementary receiver in the CMTS demodulator are theoreticallyprovisioned for identical frequencies, frequency offsets may occur for avariety of reasons. These reasons include errors in the localoscillators of the CM modulator (used to transmit the signal burst atthe provisioned frequency) or CMTS front-end (used to down-convert thereceived signal burst to baseband) as well as the use of up- anddownconversion processes applied to the upstream channels over the pathfrom CM to CMTS. These conversion processes are used to combine andsplit multiple channels over common communication paths for economictransport. Depending on severity and other system issues, frequencyoffsets could degrade Bit Error Rates (BERs), increase latencies, orcompletely prevent signal capture. However, these problems may beavoided by using closed loop methods to minimize or eliminate theoffsets.

[0005] In CMTS applications, system operation may be conceptuallydivided into normal data traffic conditions (traffic mode) and so-calledranging periods (ranging mode). Ranging is a closed loop process bywhich the CMTS manages the timing, power level, offset frequency, andequalization for the transmitter of each CM. Ranging is performedwhenever a CM is initialized and registered by the network and alsoperiodically (at regular time intervals) to update its calibration. Theranging calibration process is performed for every CM on the channel andenables the system to smoothly operate at high effective throughputduring traffic mode.

[0006] As applicable to the cable system of FIG. 1A, during ranging, aFrequency Offset Estimate 1300 is made in Demodulator 1000 of the CMTSand provided to the Control, MAC, and Framing 2000. The controlfunctions of this block then send one or more commands downstream to thecorresponding CM, remotely adjusting its transmitter frequency until thefrequency offset observed at Demodulator 1000 is reduced to withinpredefined acceptable limits. Once set during ranging, the offsetfrequency adjust continues to be used by the CM during subsequenttraffic mode operation. The ranging determined offset frequency adjustthus effectively eliminates any frequency offset observed by the CMTS,regardless of the source or sources of the offset.

[0007] Ranging represents the most problematic operating condition fordetermining the frequency offset estimate, as the frequency offset isgenerally large during ranging and other CM characteristics are not yetcalibrated for optimal performance. Accordingly, symbol errors may befrequent. During traffic mode, the CM is operating with a much smallereffective frequency offset due to the compensating offset frequencyadjust assigned by the CMTS during ranging and overall CM operation isoptimally calibrated. Symbol errors are significantly reduced.

[0008] Demodulator Operation

[0009]FIG. 2A provides a general conceptual block diagram of the digitalburst Demodulator 1000 in the CMTS 500. Front-End 600 isolates onemodulated carrier from the carrier multiplex in the Received Spectrum1100, baseband converts the signal, and passes the resulting signal 1105to the Burst and Timing Synchronization circuit 1500. (In other contextsthe Front-End 600 might be considered as a function prior to, and notpart of, the demodulator.) The Recovered Signal Samples 1106, at theoutput of circuit 1500, are discrete signal samples at the symbol rate.

[0010] Equalizer 1600 compensates for signal distortion not compensatedby a pre-equalizer in the cable modem (CM) and also suppresses ingressnoise. At the output of this stage, the Equalized Signal Samples r_(k)(1107) are given by:

r _(k) =a _(k) e ^(jσ) ^(_(k)) +w _(k),

[0011] where a_(k) is the transmitted symbol and Wk is the additivenoise. These samples are not yet synchronized in terms of carrier phase.

[0012] Carrier Phase Synchronized Samples 1108 are produced by theRotator 1700 in conjunctions with Phase Estimator 1900. The carrierphase σ_(k) given by:

σ_(k)=2kπΔfT _(s)+σ₀.

[0013] where Δf is the frequency offset and T_(s) is the symbol period.

[0014] Let {circumflex over (σ)}_(k) be the estimated carrier phase usedfor symbol k. The equalized signal r_(k) is multiplied byexp(−j{circumflex over (σ)}_(k)) within Rotator 1700 so as to decidesymbol a_(k) by Detector 1800. The decision on symbol a_(k) is denotedd_(k), which is output as Detected Symbols 1200.

[0015] The quantity p_(k)=r_(k)d_(k)* is subsequently computed. For CMTSand other applications having a high value of the frequency drift,quasi-differential demodulation is preferred, and the carrier phaserecovery algorithm only uses the last value of p_(k) to determine thecarrier phase. In such cases, the estimated carrier phase can thus bewritten as:

{circumflex over (σ)}_(k) =arg(r _(k−1) d _(k−1)*)

[0016] Prior Art Frequency Estimators

[0017] Frequency Offset Estimator 8000 provides Frequency OffsetEstimate 1300, an estimate of the observed frequency offset of thereceived signal. Prior art frequency estimation techniques for generalburst demodulator applications have used phase slope computations andrelated time averaging, or have been based on the autocorrelationfunction of the signal. FIG. 2B illustrates a particular prior artFrequency Offset Estimator (8000-PA-AC) based on autocorrelation of thesignal. FIG. 2C illustrates a particular prior art Frequency OffsetEstimator (8000-PA-PS) based on phase slope computations. FIG. 2Dprovides additional detail of the Phase Slope Computation 8100, of FIG.2C.

[0018] The prior art frequency estimation techniques providesatisfactory precision for more general burst demodulator applicationsthat use long bursts of known symbols (such as found in long messagepreambles) or admit to time averaging over multiple consecutive bursts.Unfortunately, both isolated short bursts and symbol errors arecharacteristics of CMTS applications, particularly during ranging. CMTSapplications employ isolated short ranging bursts of approximately 200symbols, consisting of a very short preamble (typically 20-30 knownsymbols) and a short data block consisting of symbols extracted by thelocal detector. Due to noise and other factors, generally including theexistence of frequency offsets, the output of the detector will not befree of symbol errors.

[0019] In view of the above, it is useful to make a detailed examinationof the performance of the prior art frequency estimator based on theautocorrelation function of the signal. As shown in FIG. 2B, the priorart autocorrelation estimator bases the frequency estimation on thecomputation of δ_(k)=p_(k)p_(k−L)*. By proper normalization of the timeaverage of δ_(k), the frequency can be estimated as:$\hat{\Delta \quad f} = \frac{\arg \quad \left( {\sum\limits_{k = {L + 1}}^{N}\delta_{k}} \right)}{2\pi \quad T_{s}L}$

[0020] where N designates the number of symbols in the burst at hand,and L is a delay parameter defined in the Correlator 8620 in FIG. 2B.

[0021] Suppose that a symbol error occurs at the k₀ decision instant.With the assumed QPSK signal format, this leads to an instantaneousphase error of ±π/2. Furthermore, as quasi-differential demodulation isused, this ±π/2 phase-error appears in all subsequent symbol decisions,and also in all p_(k) values computed after k₀.

[0022] Thus, the phase of p_(k) for the theoretical frequency estimatorhas a constant slope except for one discontinuity of ±π/2 when the erroroccurs. Consequently, the phase of δ_(k) (recall thatδ_(k)=p_(k)p_(k−L)*) is centered around the desired value, except for Lvalues with an error of ±π/2. The average phase of δ_(k) over the burstsize is then shifted by ±L(π/2)/(N−L). Since the normalized frequencyestimate ΔfT_(s) is obtained by dividing this average phase by 2πL, itclearly contains an error of ±0.25/(N−L).

[0023] Consider a particular quantitative example using the foregoinganalysis. Suppose that we want to have an estimation precision of 10⁻⁴for a burst length of 200. Should a single decision error occur duringthis burst, this error would result in a normalized frequency estimationerror of approximately 0.25/200, or approximately 10⁻³. This is an orderof magnitude greater than the desired accuracy of 10⁻⁴. Those skilled inthe art will see that a similar analysis, with similar results, can bemade for a phase slope based estimator.

[0024] The prior art frequency estimation approaches are clearly notwell suited to CMTS applications, as it has been seen that even a singlesymbol error results in substantial errors. Improved frequencyestimation methods and devices are needed that provide precise frequencyestimates for short bursts in the presence of symbol errors. Newfrequency estimation approaches are needed that can be performed on onesingle burst, without the need for averaging the results of severalconsecutive bursts. In particular, improved frequency estimationtechniques are needed that offer superior performance for CMTSapplications.

BRIEF DESCRIPTION OF DRAWINGS

[0025]FIGS. 1A and 1B illustrate a prior-art HFC cable system. FIG. 1Ais a top-level view of the cable system. FIG. 1B provides additionaldetail of the CPE of FIG. 1A.

[0026]FIG. 2A provides internal architectural detail of Demodulator 1000of FIG. 1A.

[0027]FIG. 2B provides detail of a prior art Frequency Offset Estimator8000-PA-AC, based on Autocorrelation of the signal, and havingapplication in the Demodulator 1000 of FIG. 2A.

[0028]FIG. 2C provides detail of a prior art Frequency Offset Estimator8000-PA-PS, based on Phase Slope Computation, and having application inthe Demodulator 1000 of FIG. 2A.

[0029]FIG. 2D provides additional detail of a prior art Phase SlopeComputation Function 8100, as used in FIG. 2C.

[0030]FIG. 3 provides detail of a first illustrative embodiment(8000-AC) of a Frequency Offset Estimator, based on Autocorrelation, inaccordance with the present invention, and having application in theDemodulator of FIG. 2A. FIG. 4 provides detail of a second illustrativeembodiment (8000-PS) of a Frequency Offset Estimator, based on PhaseSlope Computation, in accordance with the present invention, and havingapplication in the Demodulator of FIG. 2A.

[0031]FIG. 5 provides detail of an illustrative embodiment of anAtypical Samples Filter 9000, suitable for application as either theDiscard Atypical Correlation Samples Function 8630 of FIG. 3, or theDiscard Atypical Phase Slope Samples Function 8200 of FIG. 4.

SUMMARY

[0032] The present invention provides methods and apparatus forgenerating precise frequency estimates for applications with both shortbursts and symbol errors. The invention is practical, easy to implement,robust against decision errors, and requires only one burst to achievefrequency estimation with high precision (around 10⁻⁴ in ΔfT_(s) in theillustrative embodiments).

[0033] The invention performs frequency estimation over both the burstpreamble, during which known symbols are transmitted, and also duringthe burst's data packet, which is subsequent to the preamble andextracted by the local detector. During the preamble, an initialfrequency estimate is obtained. This estimate is based on a time averageof either phase or correlation samples. Atypical phase or correlationsamples, attributable to detector symbol errors during the data packet,are detected and filtered, so as to avoid including the atypical samplesin a time-average used to provide the frequency estimate.

[0034] In a first embodiment correlation samples are time averaged, andatypical correlation samples are suppressed prior to correlation timeaveraging. In a second embodiment, phase slope values are time averaged,and atypical values of phase slope are suppressed prior to phase slopetime averaging.

DETAILED DESCRIPTION

[0035] Atypical Sample Suppression

[0036] Recall that in the presence of a single symbol error, the phaseof p_(k) for the prior art autocorrelation frequency estimator of FIG.2B has a constant slope except for one discontinuity of ±π/2 associatedwith the symbol error. Consequently, the phase of δ_(k) is centeredaround the desired value, except for L values with an error of ±π/2. Thepresent invention, illustrated in FIGS. 3-5, improves upon the prior artestimator by eliminating the secondary peak via appropriate non-linearfiltering. More specifically, the aim of this filtering is to eliminatefrom the integration on δ_(k) the values known to be wrong. These valuesare those whose argument differs from that of the current average ofδ_(k) by more than a certain angle ν.

[0037] In preferred embodiments a preamble of 26 known symbols is used.Thanks to the preamble, it is possible to have a first coarse frequencyestimate at the beginning of the data symbols. Using this value, it ispossible to determine for each new δ_(k) whether it should be kept ornot in the sum. If it is, this new value of the sum is used to filterthe next symbols. Thus, if the coarse estimate provided by the preambleis precise enough, the secondary peaks are totally eradicated.Simulations of the illustrative embodiments have confirmed that theprecision of the coarse frequency estimate provided by the preamble doessupport elimination of the secondary peaks. Those skilled in the artwill appreciate that while the above description has focused on theelimination of atypical correlation samples for an autocorrelationfrequency estimator, the invention is equally applicable to eliminationof atypical phase slope samples for a phase slope computation frequencyestimator.

[0038] Autocorrelation Embodiment

[0039]FIG. 3 shows an Autocorrelation Frequency Estimator (8000-AC) inaccordance with the present invention. As the name suggests, thefrequency estimation algorithm is based on the computation ofCorrelation Samples δ_(k)=p_(k)p_(k−L)* (8625), which are generated byCorrelator 8620.

[0040] The discard atypical values and time averaging functions (8630and 8640, respectively) operate on an exponential function involving thephase slope. At the output of the Correlation Time Averaging stage 8640,we have ρ_(k)exp(j2πLΔf_(k)T) 8645, where atypical values have beensuppressed by Discard Atypical Correlation Samples 8630. DiscardAtypical Correlation Samples 8630 acts such that δ_(k) has no effect onthe running time average whenever the absolute value of arg[δ_(k)exp(−j2πLΔf_(k)T)] is greater than a fixed threshold ν.

[0041] Arg(.) 8650 delivers the phase 2πLΔf_(k)T, which is used asunnormalized frequency offset estimate 1300-U. Normalized frequencyoffset estimate 1300-N may optionally be provided as output.

[0042] Phase Slope Computation Embodiment

[0043]FIG. 4 shows a Phase Slope Computation Frequency Estimator(8000-PS) in accordance with the present invention. The Phase SlopeComputation 8100 of FIG. 2D, is preferably used as the first stage ofthe improved Frequency Estimator (8000-PS) of FIG. 4. Within said PhaseSlope Computation 8100, the received signal r_(k) 1107 is multiplied(via 8105) by the complex conjugate of the detected symbol d_(k) 1200.The function Arg(.) (i.e., the phase calculation function) 8120 givesthe phase difference 8110 between the received and detected signals.Slope Computation 8140 computes the phase slope 8150 from twophase-values separated by L samples.

[0044] Phase Slope Time Averaging 8300 outputs an estimate of thefrequency offset 2πΔf_(k)T (1300-U) using the phase slope valuescomputed up to time k. This unnormalized frequency offset, or thenormalized frequency offset estimate Δf_(k) (1300-N), is updated at thesymbol rate.

[0045] Discard Atypical Phase Slope Samples 8200 acts to discard theinstantaneous phase slope values 8150 which differ from the currentunnormalized frequency offset estimate 2πΔf_(k)T (1300-U) by more than afixed threshold μ. If the difference between the two signals exceeds μ,then this circuit decides that a symbol error has occurred and that thecurrent slope value should not be included in the time-averagingfunction. That is, λ_(k) has no effect on the running time averagewhenever the absolute value of 2πΔf_(k)T-λ_(k) is greater than μ. Eitherthe unnormalized frequency offset 1300-U or normalized frequency offsetestimate 1300-N may be provided as output to the Control, MAC, Framing2000 block of CMTS 500.

[0046] Atypical Samples Filter

[0047]FIG. 5 provides detail of a conceptual illustrative embodiment ofan Atypical Samples Filter 9000, suitable for application as either theDiscard Atypical Correlation Samples Function 8630 of FIG. 3, or theDiscard Atypical Phase Slope Samples Function 8200 of FIG. 4. Thisfilter acts such that the current sample 9010 has no effect on therunning time average of samples whenever the absolute value of thedifference between the time average of samples 9020 and current sample9010 is greater than the typical sample variance 9040. Block 9200compares Current Sample 9010 with Time Average Of Samples 9020 togenerate Current Sample Variance 9250. This in turn is compared againstpredefined Typical Sample Variance 9040 to produce Current Sample isTypical 9350, a logical binary valued control output. This control canbe used directly by a subsequent time averaging circuit toqualify/suppress the use of the current sample. Alternatively, or incombination with direct use, this control can be used to zero the FilterSample value 9060 provided to the time averaging circuit.

[0048] Implementation Considerations

[0049] In comparing the two illustrative embodiments, the phase functionon which the phase slope based estimator of FIG. 4 operates is a“wrapped” function that is periodic between −π and +π. The significanceof this is that boundary tests and conditional calculations must beperformed to “unwrap” this function prior to the computation of thephase slope and thereby the frequency offset. The correlation-basedestimator of FIG. 3 has no need to perform the extra phase unwrappingoperations, and thus may offer implementation advantages.

[0050] In considering the implementation boundary between hardware (H/W)and software (S/W), remember that the Demodulator 1000 of FIG. 1A doesnot use the frequency estimation result. Instead it is sent by the CMTSto the CM as an offset-frequency-adjust to control the CMtransmit-frequency. This is not a real time procedure, and only oneoffset frequency adjust is to be sent per burst. However, the frequencyerror estimate is extracted from a real-time sampled signal with onesample per symbol. In our preferred implementation, all functions areimplemented in hardware except the phase calculation in box 8650 andoptional normalization in box 8660 of FIG. 3, and the optionalnormalization in box 8400 in FIG. 4. The reason is that thosecomputations are performed once per burst, which means that they do notneed high-speed electronics.

[0051] A fully software implementation would consist of sending theequalized samples r_(k) and detected symbols d_(k) to the software andmake all computations in software. While such an implementation iswithin the scope of the present invention, it is not likely to be anefficient implementation. In general, real-time computations (at thesymbol rate) are best made in hardware and low-speed computations (atthe burst rate) are best made in software.

Conclusion

[0052] Although the present invention has been described usingparticular illustrative embodiments, it will be understood that manyvariations in construction, arrangement and use are possible consistentwith the teachings and within the scope of the invention. For example,bit-widths, clock speeds, and the type of technology used may generallybe varied in each component block of the invention. Also, unlessspecifically stated to the contrary, the value ranges specified, themaximum and minimum values used, or other particular specifications(such as the desired accuracy of the frequency estimate), are merelythose of the illustrative or preferred embodiments, can be expected totrack improvements and changes in implementation technology, and shouldnot be construed as limitations of the invention. Functionallyequivalent techniques known to those skilled in the art may be employedinstead of those illustrated to implement various components orsub-systems. It is also understood that many design functional aspectsmay be carried out in either hardware (i.e., generally dedicatedcircuitry) or software (i.e., via some manner of programmed controlleror processor), as a function of implementation dependent designconstraints and the technology trends of faster processing (whichfacilitates migration of functions previously in hardware into software)and higher integration density (which facilitates migration of functionspreviously in software into hardware).

[0053] Specific variations within the scope of the invention include,but are not limited to: the use of any of a variety of techniques foridentifying atypical samples and for suppressing their impact on sampleaverages, the use of any of a variety of preamble lengths and not justvia the preferred length of 26 symbols, and the use of either or both ofthe unnormalized and normalized frequency offset.

[0054] All such variations in design comprise insubstantial changes overthe teachings conveyed by the illustrative embodiments. The names givento interconnect and logic are illustrative, and should not be construedas limiting the invention. It is also understood that the invention hasbroad applicability to other communications and network applications,and is not limited to the particular application or industry of theillustrated embodiments. The present invention is thus to be construedas including all possible modifications and variations encompassedwithin the scope of the appended claims.

We claim:
 1. A subsystem for estimating the frequency offset between atransmitter and a receiver, the receiver having signals includingpre-detection signal samples and detected symbols, the subsystemcomprising: a) a first processing stage, coupled to the pre-detectionsignal samples and the detected symbols, the first processing stagegenerating first processed samples; b) a time averaging stage, having asamples input and a first estimate indication output, the first estimateindication being a time average of the input samples; and c) an atypicalsamples stage, coupled to receive the first processed samples and thefirst estimate indication, the atypical samples stage having a samplestatus indication selectively characterizing particular first processedsamples as typical.
 2. The subsystem of claim 1, further wherein thesample status indication is coupled to the time averaging stage tosuppress inclusion of atypical samples.
 3. The subsystem of claim 2,further wherein the samples input of the time average stage is coupledto an output of the atypical samples stage.
 4. The subsystem of claim 1,further wherein the atypical samples stage provides filtered samples tothe samples input of the time average stage, the samples being generatedfrom the first processed samples by suppressing atypical samples.
 5. Thesubsystem of claim 4, wherein zero samples are substituted for theatypical samples to perform the suppression.
 6. The subsystem of claim5, wherein the substitution is performed using a signal multiplexor. 7.The subsystem of claim 6, wherein the multiplexor is controlled by thesignal status indication.
 8. The subsystem of claim 1, wherein theatypical samples stage creates an intermediate current sample variance.9. The subsystem of claim 1, wherein the atypical samples stage performsfirst and second comparison operations, wherein the first comparisonoperation evaluates the current sample against the average of previoussamples and creates a current sample variance, and the second comparisonoperation evaluates the current sample variance against a typical samplevariance.
 10. The subsystem of claim 1, wherein the first processingstage includes a correlator and the first processed samples arecorrelation samples.
 11. The subsystem of claim 10, further including aphase calculation stage having an input coupled to the first estimateindication and generating a second estimate indication, the secondestimate indication providing an unnormalized frequency offset estimate.12. The subsystem of claim 11, further including a normalization stagehaving an input coupled to the second estimate indication and generatinga third estimate indication, the third estimate indication providing anormalized frequency offset estimate.
 13. The subsystem of claim 1,wherein the first processing stage performs a phase slope computation,the first processed samples are phase slope samples, and the firstestimate indication provides an unnormalized frequency offset estimate.14. The subsystem of claim 13, further including a normalization stagehaving an input coupled to the first estimate indication and generatinga second estimate indication, the second estimate indication providing anormalized frequency offset estimate.
 15. The subsystem of claim 13,wherein the phase slope computation includes a phase calculationsub-stage and a slope computation sub-stage.
 16. The subsystem of claim1, wherein the subsystem is operated over both the burst preamble andduring the burst's data packet, and wherein the atypical samples stagedoes not suppress samples during at least part of the burst preamble.17. The subsystem of claim 16, wherein the preamble uses 26 knownsymbols.
 18. The subsystem of claim 16, wherein the atypical samplesstage does not suppress samples over the entire burst preamble.
 19. Amethod of estimating a frequency offset between a transmitter and areceiver based on the received spectrum at the receiver, the transmittersending the receiver bursts having a preamble and data, the methodcomprising: a) providing processed samples derived from the receivedspectrum, including a current sample; b) providing a typical samplevariance; c) generating a time average of the processed samples; and d)during the burst data, excluding the current sample in the time averagewhen the difference between the current sample and the time averageexceeds the typical sample variance.
 20. The method of claim 19, furtherincluding: during the burst preamble, including the current sample inthe time average.
 21. The method of claim 20, wherein the preamble uses26 known symbols.
 22. The method of claim 20, wherein the processedsamples are correlation samples.
 23. The method of claim 22, furtherincluding calculating the phase of the time average to provide anunnormalized frequency offset estimate.
 24. The method of claim 23,further including performing normalization to provide a normalizedfrequency offset estimate.
 25. The method of claim 20, wherein theprocesses samples are phase slope samples and the time average providesan unnormalized frequency offset estimate.
 26. The method of claim 25,further including performing normalization to provide a normalizedfrequency offset estimate.
 27. A burst demodulator for a receiver, thereceiver receiving bursts from a transmitter, the burst demodulatorcomprising: a) a stage generating pre-detection signal samples; b) adetector stage generating detected symbols; and c) a subsystem forestimating the frequency offset between the transmitter and thereceiver, the subsystem including i. a first processing stage, coupledto the pre-detection signal samples and the detected symbols, the firstprocessing stage generating first processed samples; ii. a timeaveraging stage, having a samples input and a first estimate indicationoutput, the first estimate indication being a time average of the inputsamples; and iii. an atypical samples stage, coupled to receive thefirst processed samples and the first estimate indication, the atypicalsamples stage having a sample status indication selectivelycharacterizing particular first processed samples as typical.
 28. Theburst demodulator of claim 27, wherein the first processing stageincludes a correlator and the first processed samples are correlationsamples.
 29. The burst demodulator of claim 28, further including aphase calculation stage having an input coupled to the first estimateindication and generating a second estimate indication, the secondestimate indication providing an unnormalized frequency offset estimate.30. The burst demodulator of claim 29, further including a normalizationstage having an input coupled to the second estimate indication andgenerating a third estimate indication, the third estimate indicationproviding a normalized frequency offset estimate.
 31. The burstdemodulator of claim 27, wherein the first processing stage performs aphase slope computation, the first processed samples are phase slopesamples, and the first estimate indication provides an unnormalizedfrequency offset estimate.
 32. The burst demodulator of claim 31,further including a normalization stage having an input coupled to thefirst estimate indication and generating a second estimate indication,the second estimate indication providing a normalized frequency offsetestimate.
 33. The burst demodulator of claim 31, wherein the phase slopecomputation includes a phase calculation sub-stage and a slopecomputation sub-stage.
 34. The burst demodulator of claim 27, whereinthe subsystem is operated over both the burst preamble and during theburst's data packet, and wherein the atypical samples stage does notsuppress samples during at least part of the burst preamble.
 35. Theburst demodulator of claim 34, wherein the preamble uses 26 knownsymbols.
 36. The burst demodulator of claim 34, wherein the atypicalsamples stage does not suppress samples over the entire burst preamble.37. A cable modem termination system (CMTS) for a cable system, thecable system including at least one cable modem having a transmitter,the CMTS comprising: a) a modulator; b) a network interface includingcontrol, media-access-control, and framing functions; and c) ademodulator coupled to receive bursts from the cable modem transmitter,the demodulator including a stage generating pre-detection signalsamples, a detector stage generating detected symbols, and a subsystemfor estimating the frequency offset between the cable modem transmitterand the demodulator, the subsystem including i. a first processingstage, coupled to the pre-detection signal samples and the detectedsymbols, the first processing stage generating first processed samples;ii. a time averaging stage, having a samples input and a first estimateindication output, the first estimate indication being a time average ofthe input samples; and iii. an atypical samples stage, coupled toreceive the first processed samples and the first estimate indication,the atypical samples stage having a sample status indication selectivelycharacterizing particular first processed samples as typical.
 38. TheCMTS of claim 37, wherein the first processing stage includes acorrelator and the first processed samples are correlation samples. 39.The CMTS of claim 38, further including a phase calculation stage havingan input coupled to the first estimate indication and generating asecond estimate indication, the second estimate indication providing anunnormalized frequency offset estimate.
 40. The CMTS of claim 39,further including a normalization stage having an input coupled to thesecond estimate indication and generating a third estimate indication,the third estimate indication providing a normalized frequency offsetestimate.
 41. The CMTS of claim 37, wherein the first processing stageperforms a phase slope computation, the first processed samples arephase slope samples, and the first estimate indication provides anunnormalized frequency offset estimate.
 42. The CMTS of claim 41,further including a normalization stage having an input coupled to thefirst estimate indication and generating a second estimate indication,the second estimate indication providing a normalized frequency offsetestimate.
 43. The CMTS of claim 41, wherein the phase slope computationincludes a phase calculation sub-stage and a slope computationsub-stage.
 44. The CMTS of claim 27, wherein the subsystem is operatedover both the burst preamble and during the burst's data packet, andwherein the atypical samples stage does not suppress samples during atleast part of the burst preamble.
 45. The CMTS of claim 44, wherein thepreamble uses 26 known symbols.
 46. The CMTS of claim 44, wherein theatypical samples stage does not suppress samples over the entire burstpreamble.
 47. A method of adjusting the frequency of a cable modem, thecable modem having a transmitter that sends bursts to the demodulator ofa cable modem termination system, the bursts having a preamble and data,the demodulator having a received spectrum at its input, the methodcomprising: a) commanding the cable modem to operate in ranging mode; b)providing processed samples derived from the received spectrum, theparticular processed sample at the current time being referred to as thecurrent sample; c) defining a typical sample variance and an acceptablefrequency offset limit; d) generating a running time average of theprocessed samples; e) during the burst preamble, including the currentsample in the time average; f) during the burst data, excluding thecurrent sample in the time average when the difference between thecurrent sample and the time average exceeds the typical sample variance;g) deriving a frequency offset estimate from the time average; and h)commanding the cable modem to adjust its transmit frequency until thefrequency offset estimate is reduced to within the frequency offsetlimit.
 48. The method of claim 47, wherein the preamble uses 26 knownsymbols.
 49. The method of claim 47, wherein the processed samples arecorrelation samples.
 50. The method of claim 49, wherein the derivationof the frequency offset estimate includes calculating the phase of thetime average.
 51. The method of claim 50, wherein the derivation of thefrequency offset estimate further includes performing normalization onthe phase calculation result.
 52. The method of claim 47, wherein theprocesses samples are phase slope samples.
 53. The method of claim 52,wherein the derivation of the frequency offset estimate includesperforming normalization on the time average.